{"id":"https://openalex.org/W3010603606","doi":"https://doi.org/10.1109/wacv45572.2020.9093296","title":"Lane detection using lane boundary marker network with road geometry constraints","display_name":"Lane detection using lane boundary marker network with road geometry constraints","publication_year":2020,"publication_date":"2020-03-01","ids":{"openalex":"https://openalex.org/W3010603606","doi":"https://doi.org/10.1109/wacv45572.2020.9093296","mag":"3010603606"},"language":"en","primary_location":{"id":"doi:10.1109/wacv45572.2020.9093296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5018793102","display_name":"Hussam Ullah Khan","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Hussam Ullah Khan","raw_affiliation_strings":["KeepTruckin Inc. (RnD), Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"KeepTruckin Inc. (RnD), Lahore, Pakistan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5027102466","display_name":"Afsheen Rafaqat Ali","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Afsheen Rafaqat Ali","raw_affiliation_strings":["KeepTruckin Inc. (RnD), Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"KeepTruckin Inc. (RnD), Lahore, Pakistan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038396659","display_name":"Ali Hassan","orcid":"https://orcid.org/0000-0003-1667-7166"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ali Hassan","raw_affiliation_strings":["KeepTruckin Inc. (RnD), Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"KeepTruckin Inc. (RnD), Lahore, Pakistan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100693435","display_name":"Ahmed Ali","orcid":"https://orcid.org/0000-0002-9186-7544"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ahmed Ali","raw_affiliation_strings":["KeepTruckin Inc. (RnD), Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"KeepTruckin Inc. (RnD), Lahore, Pakistan","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5073113179","display_name":"Wajahat Kazmi","orcid":"https://orcid.org/0000-0002-4608-6810"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wajahat Kazmi","raw_affiliation_strings":["KeepTruckin Inc. (RnD), Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"KeepTruckin Inc. (RnD), Lahore, Pakistan","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005282226","display_name":"Aamer Zaheer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aamer Zaheer","raw_affiliation_strings":["KeepTruckin Inc. (RnD), Lahore, Pakistan"],"affiliations":[{"raw_affiliation_string":"KeepTruckin Inc. (RnD), Lahore, Pakistan","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5018793102"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":1.5098,"has_fulltext":false,"cited_by_count":20,"citation_normalized_percentile":{"value":0.82004357,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1823","last_page":"1832"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12549","display_name":"Image and Object Detection Techniques","score":0.9902999997138977,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/equidistant","display_name":"Equidistant","score":0.8454280495643616},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.6876170635223389},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6627194881439209},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6528513431549072},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.579072892665863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.546755850315094},{"id":"https://openalex.org/keywords/detector","display_name":"Detector","score":0.5243297219276428},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4726354479789734},{"id":"https://openalex.org/keywords/range","display_name":"Range (aeronautics)","score":0.42781922221183777},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4239111840724945},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3809199631214142},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.359738826751709},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3366817533969879},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24092069268226624},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11478486657142639}],"concepts":[{"id":"https://openalex.org/C158245278","wikidata":"https://www.wikidata.org/wiki/Q4386982","display_name":"Equidistant","level":2,"score":0.8454280495643616},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.6876170635223389},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6627194881439209},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6528513431549072},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.579072892665863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.546755850315094},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.5243297219276428},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4726354479789734},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.42781922221183777},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4239111840724945},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3809199631214142},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.359738826751709},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3366817533969879},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24092069268226624},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11478486657142639},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/wacv45572.2020.9093296","is_oa":false,"landing_page_url":"https://doi.org/10.1109/wacv45572.2020.9093296","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE Winter Conference on Applications of Computer Vision (WACV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.7699999809265137,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":41,"referenced_works":["https://openalex.org/W1820781151","https://openalex.org/W1903029394","https://openalex.org/W1966151866","https://openalex.org/W2040046539","https://openalex.org/W2042086752","https://openalex.org/W2085261163","https://openalex.org/W2104241941","https://openalex.org/W2116484457","https://openalex.org/W2118545852","https://openalex.org/W2136756158","https://openalex.org/W2152422345","https://openalex.org/W2157307166","https://openalex.org/W2163605009","https://openalex.org/W2165574152","https://openalex.org/W2169900545","https://openalex.org/W2194775991","https://openalex.org/W2275957239","https://openalex.org/W2478820856","https://openalex.org/W2482325425","https://openalex.org/W2513332682","https://openalex.org/W2738638456","https://openalex.org/W2745410201","https://openalex.org/W2780740184","https://openalex.org/W2895707844","https://openalex.org/W2896929926","https://openalex.org/W2903637353","https://openalex.org/W2913723144","https://openalex.org/W2963150697","https://openalex.org/W2963611454","https://openalex.org/W2963881378","https://openalex.org/W2964199920","https://openalex.org/W2964332990","https://openalex.org/W2981441441","https://openalex.org/W3009604100","https://openalex.org/W3102168793","https://openalex.org/W4285719527","https://openalex.org/W6684191040","https://openalex.org/W6694492492","https://openalex.org/W6721735011","https://openalex.org/W6747394537","https://openalex.org/W6759311492"],"related_works":["https://openalex.org/W2055230676","https://openalex.org/W2373708349","https://openalex.org/W2370379095","https://openalex.org/W2064284991","https://openalex.org/W2385837322","https://openalex.org/W2123581415","https://openalex.org/W2546071705","https://openalex.org/W847106846","https://openalex.org/W2969228573","https://openalex.org/W2963690996"],"abstract_inverted_index":{"Lane":[0],"detection":[1],"is":[2,78,84],"of":[3,24,42,133,138],"critical":[4],"importance":[5],"to":[6,28,46,67,87,177],"both":[7,157],"the":[8,40,55,71,88,97,142],"self-driving":[9],"cars":[10],"as":[11,13],"well":[12],"advanced":[14],"driver":[15],"assistance":[16],"systems.":[17],"While":[18],"current":[19],"methods":[20],"use":[21,61],"a":[22,62,130],"range":[23],"features":[25,30],"from":[26,32,39],"low-level":[27],"deep":[29],"extracted":[31],"convolutional":[33],"neural":[34],"networks,":[35],"they":[36],"all":[37],"suffer":[38],"problem":[41],"occlusion":[43],"and":[44,91,112,136,147,159],"struggle":[45],"detect":[47,68],"lanes":[48,161],"with":[49,120,173],"low":[50],"or":[51],"no":[52],"evidence":[53,122],"on":[54,96,144],"road.":[56],"In":[57],"this":[58],"paper,":[59],"we":[60,164],"lane":[63,72,102,107,118,175,180],"boundary":[64],"marker":[65],"network":[66],"keypoints":[69],"along":[70],"boundaries.":[73],"An":[74],"inverse":[75],"perspective":[76],"mapping":[77],"estimated":[79],"using":[80,106],"road":[81],"geometry":[82,108],"which":[83],"then":[85],"applied":[86],"detected":[89],"markers":[90],"lines/curves":[92],"are":[93,104],"fitted":[94],"jointly":[95],"rectified":[98],"points.":[99],"Finally,":[100],"missing":[101,160],"boundaries":[103,119],"predicted":[105,125],"constraints":[109],"i.e.,":[110],"equidistant":[111],"parallelism.":[113],"Reciprocal":[114],"weighted":[115],"averaging":[116],"ensures":[117],"strong":[121],"dominate":[123],"their":[124,179],"alternatives.":[126],"The":[127],"results":[128],"show":[129,166],"significant":[131],"improvement":[132],"+7.8%,":[134],"+6.8%":[135],"+1.2%":[137],"F1":[139],"scores":[140],"over":[141],"state-of-the-art":[143],"CU-Lane,":[145],"Caltech":[146],"TuSimple":[148],"datasets,":[149],"respectively.":[150],"This":[151],"proves":[152],"our":[153,168],"algorithm's":[154],"robustness":[155],"against":[156],"occluded":[158],"cases.":[162],"Furthermore,":[163],"also":[165],"that":[167],"algorithm":[169],"can":[170],"be":[171],"combined":[172],"other":[174],"detectors":[176],"improve":[178],"retrieval":[181],"potential.":[182]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":7},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
